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Multiscale analysis of compartment models with dispersal
Yun Kang1, Carlos Castillo-Chavez
1Applied Sciences and Mathematics, Arizona State University, Mesa, AZ 85212, USA. yun.kang@asu.edu
Journal of Biological Dynamics
|September 1, 2012
Summary
Disease significantly impacts animal population dynamics and dispersal, especially when considering Allee effects and spatial variations. Initial conditions and landscape connectivity are crucial for understanding population persistence and spread.
Area of Science:
- Ecology
- Population Dynamics
- Epidemiology
Background:
- Animal population dynamics and dispersal are fundamental ecological processes.
- The interplay between disease, population dynamics, and spatial structure is complex and requires further investigation.
- Allee effects, where population growth rate decreases at low densities, can be influenced by disease and spatial factors.
Purpose of the Study:
- To investigate the impact of dispersal on population dynamics in the presence of disease.
- To analyze how induced Allee effects, disease dynamics, and spatial heterogeneity interact.
- To explore the role of initial conditions, patch quality, and landscape connectivity in disease-influenced populations.
Main Methods:
- Utilized deterministic and stochastic mathematical models.
- Incorporated disease-driven effects on competition, movement, and reproduction.
- Examined the influence of spatial heterogeneity and landscape structure.
Main Results:
- Dispersal significantly alters population dynamics when disease is present.
- Initial conditions and patch quality critically influence population persistence.
- Landscape connectivity and 'topological' structure play a key role in disease spread and population viability.
- Disease acts as a significant selective force shaping population dynamics.
Conclusions:
- Disease is a crucial factor modulating the effects of dispersal and spatial heterogeneity on population dynamics.
- Understanding landscape connectivity is vital for managing populations in disease-endemic areas.
- The study highlights the importance of integrating disease ecology into population viability analyses.
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